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Trial Title
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Before
Linking emotional priming to information provision– Differential effects on valuation for sustainable alternatives, by sustainability objective and market product
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After
Emotional priming for sustainable consumption? Differential effects on valuation of labelled chocolate
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Trial Status
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Before
in_development
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on_going
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Abstract
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Before
Current food choices are unsustainable: most food products have social and environmental consequences that harm current and future generations worldwide. Recent studies analyzed the determinants driving sustainable food choices and experimentally tested ways to increase consumers’ willingness-to-pay for sustainability certifications. Thereby, little is known about how the average consumer can be reached best. Insights about the potential of emotionally primed information, as commonly used in brand marketing and donation calls, suggests that the use of emotion can serve as an efficient tool of mass communication by reaching not only a niche market but the average consumer. Thus, the effects of linking information to emotional priming on the greater valuation of sustainable products are not well understood. To answer whether emotional priming in information provision increases consumers’ valuation of sustainable foods, we conduct an online experiment with 3,500 German consumers. We randomly assign information treatments related to either (1) social responsibility or (2) environmental sustainability. Each information treatment is delivered (a) with an emotional primer and (b) without. Using a discrete choice experiment and multinomial logit models, we estimate the effects of emotional priming on consumers’ willingness-to-pay for sustainability attributes, by sustainability objectives and sustainability claims in the short-and medium-term. We contribute to the existing literature in three ways by considering long-term treatment effects, social and environmental sustainability, and different product alternatives. Our findings will have high relevance for policy makers, NGOs and companies because it provides insights for social marketing campaigns to promote sustainable consumption patterns.
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After
Current food choices are unsustainable: most food products have social and environmental consequences that harm current and future generations worldwide. Recent studies analyzed the determinants driving sustainable food choices and experimentally tested ways to increase consumers’ willingness-to-pay for sustainability certifications. Thereby, evidence is scarce of how to reach the average consumer effectively. Insights into the potential of emotionally primed information - as commonly used in brand marketing and donation calls - suggest that the use of emotions serves as an efficient tool of mass communication by reaching the average consumer, not only a niche market. Thus, the effects of linking information to emotional priming on the greater valuation of sustainable products are not well understood. To answer whether emotional priming in information provision increases consumers’ valuation of sustainable foods, we conduct an online experiment with 3,500 German consumers. We randomly assign information treatments related to either (1) social responsibility or (2) environmental sustainability. Each information treatment is delivered (a) with an emotional primer and (b) without. Using a discrete choice experiment and random parameters multinomial logit models, we estimate the effects of emotional priming on consumers’ willingness-to-pay for sustainability attributes, by sustainability objectives and sustainability claims in the short-and medium-term. We contribute to the existing literature in three ways by considering long-term treatment effects, social and environmental sustainability, and different product alternatives. Our findings are relevant for policymakers, NGOs, and companies because it provides insights for social marketing campaigns to promote sustainable consumption patterns.
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Trial End Date
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Before
February 28, 2022
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July 31, 2022
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Last Published
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December 10, 2021 03:12 PM
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May 04, 2022 06:23 AM
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Intervention Start Date
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January 16, 2022
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May 06, 2022
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Intervention End Date
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January 30, 2022
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June 30, 2022
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Primary Outcomes (End Points)
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Before
The most important outcome to test the stated expectations is the consumers’ marginal willingness-to-pay (MWTP) for each one of the varying sustainability attributes in a discrete choice experiment. The MWTP corresponds to the marginal rate of substitution (MRS) between one attribute and price.
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After
The most important outcome to test the stated expectations is the consumers’ marginal WTP for each one of the varying sustainability attributes. The marginal WTP corresponds to the marginal rate of substitution (MRS) between one attribute and price.
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Primary Outcomes (Explanation)
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Before
The implicit price, MWTP of each attribute (or better MWTP for no certification or no claim to a certification or a claim), is calculated as the MRS with respect to price. The MWTP of each attribute is the ratio of the coefficient of each attribute and the coefficient of price. Its unit is Euro. We assume a linear utility function and no heterogeneity in MWTP for different characteristics of the observations. We use the Krinsky-Robb parametric bootstrapping method to calculate standard errors and 95% confidence intervals.
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After
As we are using the random parameters multinomial logit (RPL) model, we cannot use a simple ratio to estimate the marginal WTP. Instead, we reparametrize the RPL to the WTP space by using maximum simulated likelihood like in Train and Weeks to derive marginal WTP of each attribute (or better marginal WTP for no certification or no claim to a certification or a claim).
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Planned Number of Observations
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3,500 participants or 28,000 (8 times 3,500) observed choices
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3,500 participants
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Power calculation: Minimum Detectable Effect Size for Main Outcomes
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Before
As our focus lies on the outcomes of the discrete choice experiment, we only conduct power calculations for the utility outcomes using a multinomial logit and assuming linear factors of all attributes.
Using the approach by de Bekker-Grob et al. that meets the requirements of the complexity of discrete choice experiments, we estimated the minimum sample size required for each treatment group. We assumed a 95%-significance level \alpha, a statistical power level (1-β) of 80% and a multinomial logit model with only linear effects. We selected the previously mentioned chosen discrete choice design with 32 blocks, 256 total choice sets, 4 alternatives per choice set, and priors of either 0.01 or 0.05 of estimated attribute effects for the sample size calculations. As we do not have any results from pilot studies yet, we used a fixed belief about parameter values that ranged from 0.05 to 0.01 for all attribute effects. The sample size ranges from 42 for parameter priors at 0.05 to 1088 for parameter priors at 0.01. In case of the parameters around 0.05 our total sample of 3,500 participants would be large enough to accommodate the required sample sizes for each of the four treatment groups. However, if all parameters are as small as 0.01, we would have to consider to reduce the number of treatments to achieve an adequate sample size. In our pilot study we will elicit real parameter effect sizes to be able to calculate the required sample sizes and prior to that discrete choice designs more accurately.
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After
The sample size is terminated by the available funds, 3,500 participants, i.e. 875 participants in each of the four treatment arms. As our focus lies on the outcomes of the discrete choice experiment, we only concentrate on the power calculations for the utility outcomes. According to the rule of thumb by Johnson and Orme, this sample size should be a large enough sample to detect statistically significant main effects. In our case with c= 4 (largest number of levels of any attribute), t= 4 (number of choice tasks), and a=3 (number of alternatives), N needs to be larger than 167.
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Secondary Outcomes (End Points)
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Before
We consider five other outcomes. Two are related to the MWTP measure: utility and predicted unconditional and conditional market shares for each of 16 chocolate bars that are used in the discrete choice experiment.
We also consider other outcomes: the willingness-to-purchase, recall attention frequency of certified and uncertified sustainability claims on products, and emotions triggered by the treatments.
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After
We consider four other outcomes: utility, willingness-to-purchase, recall attention frequency of certified and uncertified sustainability claims on products, and emotions triggered by the treatments.
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Secondary Outcomes (Explanation)
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Before
Utility is captured as the probability of consumers to choose a certain alternative. It is estimated using a multinomial logit model for each treatment seperately.
The calculation of the unconditional and conditional market shares is based on the coefficient estimates of the multinomial logit models. We fix the price at the median of the amount participants reported to spend on chocolate in the last week across treatments. We consider the market shares of each of the 16 types of chocolate bars and the no purchasing option for the four video treatments separately. We exclude the no-purchasing option for conditional market shares. We calculate the market shares for each treatment by substituting the estimated utility coefficients into the probability equation.
A supplementary outcome is the willingness-to-purchase, a factor based on the self-reported likelihood or willingness of purchasing of one of the following four types of chocolate each: either with Fairtrade certification, Rainforest alliance certification, claim regarding social responsibility, or claim regarding environmental sustainability. We adapt the measure of self-stated likelihood or willingness to purchase Fairtrade chocolate in the future from Hansen et al. (see attached document). We also adjust the measure to a seven-point Likert-Scale. We choose to have an option of indifference despite a possible framing effect to ensure that we allow for all possible preferences of the participants. We will perform principal component analysis in order to narrow down the statement batteries to the core of the concept.
For the outcome of recall attention frequency we integrate a 14-day recall question by asking, how often they have paid attention to a number of claims or certifications in the last 14 days whilst shopping, e.g. the Nutri-Score and GMO-free labels. We include certifications and claims not related to our study so that we do not prime participants towards the certifications of interest. The categorical outcomes include seven levels of frequency.
Lastly, we capture how participants feel after watching the videos at the end of the questionnaire in the first wave and in a similar manner in the second wave. For that purpose, we employ the Discrete Emotions Questionnaire by Harmon-Jones et al. that measures anger, disgust, fear, anxiety, sadness, desire, relaxation and happiness via four items each. We will perform principal component analysis to establish continuous factors of eight groups of emotions that are based on each four components. Based on the findings in our pilot study, we will reduce the number of emotions asked for in the final survey.
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After
We will simulate the utlity of the chosen attributes using the RPL model.
A supplementary outcome is the willingness-to-purchase, a factor based on the self-reported likelihood or willingness of purchasing of one of the following four types of chocolate each: either with Fairtrade certification, Rainforest alliance certification, claim regarding social responsibility, or claim regarding environmental sustainability. We adapt the measure of self-stated likelihood or willingness to purchase Fairtrade chocolate in the future from Hansen et al. (see attached document). We also adjust the measure to a seven-point Likert-Scale. We choose to have an option of indifference despite a possible framing effect to ensure that we allow for all possible preferences of the participants. We will perform principal component analysis in order to narrow down the statement batteries to the core of the concept.
For the outcome of recall attention frequency we integrate a 14-day recall question by asking, how often they have paid attention to a number of claims or certifications in the last 14 days whilst shopping, e.g. the Nutri-Score and GMO-free labels. We include certifications and claims not related to our study so that we do not prime participants towards the certifications of interest. The categorical outcomes include seven levels of frequency.
Lastly, we capture how participants feel after watching the videos at the end of the questionnaire in the first wave and in a similar manner in the second wave. For that purpose, we employ the Discrete Emotions Questionnaire by Harmon-Jones et al. that measures anger, disgust, fear, anxiety, sadness, desire, relaxation and happiness via four items each. We will perform principal component analysis to establish continuous factors of eight groups of emotions that are based on each four components. Based on the findings in our pilot study, we will reduce the number of emotions asked for in the final survey.
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